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DBMS > Apache Impala vs. Microsoft Azure Data Explorer vs. openGauss vs. Sphinx vs. Splice Machine

System Properties Comparison Apache Impala vs. Microsoft Azure Data Explorer vs. openGauss vs. Sphinx vs. Splice Machine

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonopenGauss  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopFully managed big data interactive analytics platformAn enterprise-class RDBMS compatible with high-performance, high-availability and high-performance originally developed by HuaweiOpen source search engine for searching in data from different sources, e.g. relational databasesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSRelational DBMS infocolumn orientedRelational DBMSSearch engineRelational DBMS
Secondary database modelsDocument storeDocument store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score1.06
Rank#184  Overall
#84  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteimpala.apache.orgazure.microsoft.com/­services/­data-explorergitee.com/­opengauss
opengauss.org
sphinxsearch.comsplicemachine.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.microsoft.com/­en-us/­azure/­data-explorerdocs.opengauss.org/­en
gitee.com/­opengauss/­docs
sphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaMicrosoftHuawei and openGauss communitySphinx Technologies Inc.Splice Machine
Initial release20132019201920012014
Current release4.1.0, June 2022cloud service with continuous releases3.0, March 20223.5.1, February 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen SourceOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C, C++, JavaC++Java
Server operating systemsLinuxhostedLinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeyesFixed schema with schema-less datatypes (dynamic)yesyesyes
Typing infopredefined data types such as float or dateyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesnoyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.noyesno
Secondary indexesyesall fields are automatically indexedyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLSQL-like DML and DDL statementsKusto Query Language (KQL), SQL subsetANSI SQL 2011SQL-like query language (SphinxQL)yes
APIs and other access methodsJDBC
ODBC
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
Proprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C++
Java
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceYes, possible languages: KQL, Python, Ryesnoyes infoJava
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud servicehorizontal partitioning (by range, list and hash)Sharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replicationnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceSpark connector (open source): github.com/­Azure/­azure-kusto-sparknonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAzure Active Directory AuthenticationAccess rights for users, groups and roles according to SQL-standardnoAccess rights for users, groups and roles according to SQL-standard

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More resources
Apache ImpalaMicrosoft Azure Data ExploreropenGaussSphinxSplice Machine
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